笔记
发表于 2025-3-21 19:57:33
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无法破译
发表于 2025-3-21 22:21:27
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ETCH
发表于 2025-3-22 01:01:00
https://doi.org/10.1007/978-3-319-08114-4Bundle methods; Nondifferentiable optimization; Nonsmooth analysis; Subgradient methods; Test problems
管理员
发表于 2025-3-22 06:11:21
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女上瘾
发表于 2025-3-22 10:53:38
978-3-319-34627-4Springer International Publishing Switzerland 2014
dermatomyositis
发表于 2025-3-22 15:00:00
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军械库
发表于 2025-3-22 17:23:38
Academic Problemsion which can be and have been used to test the nonsmooth optimization software. We use a classification of test problems such that it is easy to pick up those problems that share features in interest. That is, for instance, convexity or nonconvexity, or min-max, piecewise quadratic or general polynomial objective function structure, etc.
诱导
发表于 2025-3-23 00:51:05
Hybrid Methodsods to be introduced are the . and the . for solving general small- and medium-scale nonsmooth optimization problems; the modification of variable metric bundle method for solving large-scale nonsmooth optimization problems, that is, the .; and the . for extremely large-scale convex nonsmooth optimization problems.
agnostic
发表于 2025-3-23 04:20:13
Nonconvex Analysis subdifferential, many different generalizations of the concept of a subdifferential for nonconvex nonsmooth functions exist. At the end of this chapter we briefly recall some of them. More specifically we give definitions of the quasidifferential, the codifferential, the basic (limiting) and the singular subdifferentials.
爱管闲事
发表于 2025-3-23 06:12:03
Generalized Convexitieses of the generalized pseudo- and quasiconvexities for nondifferentiable locally Lipschitz continuous functions. The treatment is based on the Clarke subdifferentials and generalized directional derivatives.